期刊
NATURE COMPUTATIONAL SCIENCE
卷 1, 期 4, 页码 280-289出版社
SPRINGERNATURE
DOI: 10.1038/s43588-021-00057-4
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资金
- NIH Medical Scientist Training Program [T32 GM07170, T32 G000046]
- Division of Intramural Research at the National Heart, Lung and Blood Institute
Clonal tracking methods provide insights into cellular output, but the lack of analysis tools has hindered standardized frameworks. The barcodeR package now offers diverse tools for analyzing and visualizing clonal tracking data, proving useful in exploring longitudinal patterns and lineage relationships in various studies.
Clonal tracking methods provide quantitative insights into the cellular output of genetically labeled progenitor cells across time and cellular compartments. In the context of gene and cell therapies, clonal tracking methods have enabled the tracking of progenitor cell output both in humans receiving therapies and in corresponding animal models, providing valuable insight into lineage reconstitution, clonal dynamics and vector genotoxicity. However, the absence of a toolbox for analysis of clonal tracking data has precluded the development of standardized analytical frameworks within the field. Thus, we developed barcodetrackR, an R package and accompanying Shiny app containing diverse tools for the analysis and visualization of clonal tracking data. We demonstrate the utility of barcodetrackR in exploring longitudinal clonal patterns and lineage relationships in a number of clonal tracking studies of hematopoietic stem and progenitor cells (HSPCs) in humans receiving HSPC gene therapy and in animals receiving lentivirally transduced HSPC transplants or tumor cells.
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